Graphrag Developer Challenge

4 settimane fa

Varese, Italia Bullaki A tempo pieno

Role Details GraphRAG Developer Challenge – Legal Document Processing (Prototype) Role : Senior RAG Systems Developer (Contract / Freelance) Compensation : $600 — paid only if you pass () 95% benchmark) Timeline : 3–5 days from materials receipt to live demo Purpose : Technical evaluation for potential long-term hire Frontend / UI : None (backend prototype only) Contact : Objective We’re seeking an expert in graph-based retrieval (GraphRAG) to build a high-accuracy prototype for legal document reasoning. This is a paid technical test that may lead to a long-term position. The goal is a true GraphRAG system featuring explicit knowledge-graph construction and traversal, multi-hop reasoning, agentic orchestration, and strong focus on retrieval accuracy and explainability. Materials Provided / docs / → Pre-processed Markdown legal documents with metadata / sample_questions.json → Example question format / sample_answers_rag.json → Example answer format Download materials : (Benchmark uses unseen questions.) Deliverables Implement two functions in Python 3.12 (Poetry project) : def ingest(document_paths: List(str)) -> None : """Ingest Markdown docs and build the knowledge graph.""" def query(questions: List(str)) -> List(str) : """Return answers with Vancouver-style citations grounded in retrieved sources.""" Requirements No UI, no API keys provided. Any stack may be used. query(...) must support parallel execution (~400 questions in ≤60 min) and show a progress indicator. Test thoroughly for correctness and performance before the demo. Live Demo In a 60-minute live session you will : Receive ~400 unseen questions. Run query(...) to produce /answers.json. Explain your architecture : how the graph is built, traversed, and used to generate grounded answers. developer(s) who wrote the code may present. Evaluation Evaluation Passing requires an overall score above 95%, measured by (LLM as a judge) : Faithfulness (grounded, no hallucinations) Relevance (retrieval matches intent) Completeness (covers key legal points) Clarity (structured, legally coherent writing) #J-18808-Ljbffr

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